Day: November 26, 2024 (Page 2 of 2)

Originally Posted May 13, 2024

“It’s the questions we can’t answer that teach us the most. They teach us how to think. If you give a man an answer, all he gains is a little fact. But give him a question and he’ll look for his own answers.” – Patrick Rothfuss

Most of us suffer from a crisis of seeing. What we can’t see, we believe we know, and that’s a problem. We need better tools for seeing, not knowing, and yet that’s what we insist on trying to turn our latest AI tools into. They don’t do that very well unless accompanied by a lot of critical seeing.

We often forget that scientific progress is based on seeing, not knowing. The scientific method always questions what we know and seeks to reconcile that with what we see. Yet we expect science to knowbecause it brought us so much knowledge.

Humans want certainty, an end to the pathway. However, any scientist worth his or her salt will quickly disabuse us of the notion that we know everything. That is because knowledge is a process of constant discovery.

However, we look to our tools for knowledge, not seeing. When we pick up a book (a tool), it’s ostensibly to gain knowledge. When we read a blog or a website (also tools), we’re doing the same. They may be connected to other containers, but those connections are often hard to perceive (a complaint about the internet shared by Tim Berners-Lee and Ted Nelson). The same is true of AI Chatbots. They’re making lots of connections behind the scenes, but we can’t see them. Seeing requires connection.

Seeing beyond the boxes of knowledge that books and website represent requires a great deal of education and practice. Most learners never get to this level and, until they do, they don’t accept that all knowledge is contextual and connected.

I tell my students that there are no right answers in my class, but there are wrong ones. This is to encourage them to explore and create, but to base that on solid foundations. I want them to explore connections, not given “facts.”

They resist this because they want to know the “right” way to do it. This is a direct product of a “learning” system has trained them to fear failure above all. You can’t see without failing.

As an author, I recognize that there are a multitude of compromises necessary to smash any set of ideas into a book, or any other textual format. When we teach the book, we rarely acknowledge what’s going on beyond the covers.

That’s because it’s hard to see those connections. You can follow citations, but that takes a lot of extra work and even they don’t fully capture the imagination of the author.

As a teacher, I recognize how hard it is to get the students to read the book in front of them, much less to acknowledge the vast number of books that exist around that book. Books risk tunnelling our vision because of how they work as narrative containers.

The tension between creativity and conformity is something that our systems of learning struggle with. I remember a conversation with my daughter’s 5th grade math teacher about a particular practice question that my daughter got “wrong.” I pointed out that the assignment worded the question badly and that there were multiple answers to it.

The teacher agreed with me that the question was problematic, but argued that there were problematic test questions on the standardized test that had to be accepted as correct because that was all that the assessment permitted. What you saw (or deduced) didn’t matter. The test itself was the knowledge that mattered and you didn’t want to “fail” that.

Part of being a good thinker is accepting uncertainty. Part of growing up is recognizing that there are many things left to be discovered. Certainty closes that door.

We equate knowledge with certainty because that’s how we learned. This is a fallacy and a corruption of what it means to be “knowledgeable.”

This corruption lies at the center of many of our struggles today. We go around expecting certainty. People wanted certainty during the pandemic, but all legitimate science could give us was a set of probabilities. The same conundrum exists as we struggle to confront the complexity of climate change. There is no certainty there, only probabilities.

However, humans crave clear narratives. Even if they are false, they provide patterns in a complex and uncertain world.

Science has moved past that. Since the discovery of first relativity and then quantum physics over a century ago, science and math realized the world does not work like Newtonian clockwork.

Observations can fool us, and we are continuously searching for better explanations. However, our quest for certainty compels us to insert mysticism where science is still searching for answers. That doesn’t mean the answers are not out there. It just means we haven’t understood them yet.

We couldn’t explain eclipses for much of human history and assigned to them a mystical value because we sought to clear up the uncertainty they aroused. Quantum physics is no different. We are equally wrong to associate it with the certainty of a belief structure to explain it.

With the flood of information we’ve unleashed through the digital revolution, our cloistered informational existences are constantly challenged. As we quest for certainty, these disconnects become ever more apparent and uncomfortable to us.

We lack the tools to see information clearly when one “definitive“ narrative conflicts with another. The current crop of generative AI tools doesn’t get there.

Asking a chatbot for difficult perspectives often triggers a host of “guardrails” to keep us from exploring uncomfortable subjects. AI companies think these guardrails are necessary because we accept their products’ answers as being “given knowledge,” not a synthesis of human conversations online.

AI Chatbots blind us to context. This is not seeing.

Generative AI reflects on us as much as anything the models are doing. Their outputs are the product of trying to create linear narratives out of a profoundly nonlinear observation. We struggle with the chaos of human existence, perceptions of systems of thought, and governance. If we build a tool that merely reflects our “knowledge” we should not be surprised if it reflects that blindness back onto us, garbage-in, garbage-out.

Our quest to know has blinded us to the possibilities of seeing. We need better tools to contextualize our ideas. As teachers, we need to teach the skills of navigating complexity rather than the skill of producing certainty. We must highlight what we don’t know as much as what we do.

New tools for thinking are necessary to facilitate this process. Books are wonderful tools for knowledge and are essential for seeing, but they have limitations as tools for perceiving the world. They can be hard tools to master. Chatbot tools merely reflect this struggle.

Like every tool, we should use them for what they are best at. However, we must look for augmented tools to help us see the world differently (and this includes the analysis of our narratives themselves). AI could provide those tools for us, but only if we design tools to take advantage of its ability to see differently rather than “know” more than us.

Originally Posted April 19, 2024

For this invention will produce forgetfulness in the minds of those who learn to use it, because they will not practice their memory. Their trust in writing, produced by external characters which are no part of themselves, will discourage the use of their own memory within them. You have invented an elixir not of memory, but of reminding; and you offer your pupils the appearance of wisdom, not true wisdom, for they will read many things without instruction and will therefore seem [275b] to know many things, when they are for the most part ignorant and hard to get along with, since they are not wise, but only appear wise. – Plato, Phaedrus (275)

This week, a topic that seems to be a repeating theme in my practice of teaching and consulting is the question of thinking. I keep hearing from faculty members that writing is thinking. As a result, their students’ ability to use generative large language models to create writing that mimics thinking threatens them.

The written word dominates our world, but it is not synonymous with thinking. Much of great thinking is not written, and too much writing contains very little thought. AI may be a threat to thoughtless writing, but it’s not a threat to thinking.

Plato argued that writing was going to destroy thinking. He wasn’t wrong. Even in ancient Greece, it democratized our ability to express ourselves, but, as King Thamus points out, that came as the cost of memory and rigor. Our ability to memorize epic poems has declined since then. Arguably, his prognostications of people using writing “to appear wise” have also borne out.

The invention of writing was not the last time technology democratized our ability to share our thinking. Gutenberg’s press prompted similar outcries as the invention of writing itself. We have heard criticisms like this again over the last few decades as writing became a digitized medium.

The digital revolution has given us all printing presses and has created a proliferation of all forms of reading and writing. This abundance has created a side effect of mediocrity. Any wag can be a pamphleteer if they have a printing press. Everyone has a printing press these days.

The reaction of the establishment was the creation of education and sets of standards that separated writing from the unwashed masses. The written word became the coin of the realm in higher education through the process of publish or perish.

This has had the unfortunate side effect of making even scholarly writing a commodity. As the educational culture forced more and more people to publish for extrinsic reasons, such as to keep their jobs, the quality of the thinking declined. Add to that financial pressure to bias research and the result is a lot of bad “scholarly thinking” that just happens to be written and passes through the peer review process.

The latest iteration of this is the discovery that people are writing scholarly works, and even books, by generating them with chat bots. Writing is no more immune to a race to the bottom than any other creative pursuit. Generative large language models do an admirable job of mimicking thoughtless writing, even in academia. They’re only going to get better at it.

As writing has become more and more ubiquitous, the limitations of thinking skills become more and more obvious. Quantity does not equal quality.

So why are we so obsessed with teaching our students to write rather than focusing on their ability to think? Writing is a quantifiable measure. One reason is extrinsic: Requiring students to write X number of words or pages for a class is something that is easy to measure. Measuring thinking is much harder.

After 20 years of teaching, I can say that quantity does not equal quality. When writing was the only way in which my students could express their thinking, this was a trade-off I had to live with. Of course, even 20 years ago, I couldn’t tell whether a student, or a sibling or parent had written the work they were turning in. Therefore, I could never be sure who was doing the thinking.

The “solution” that some have fallen back on is making more manual, in-class, writing assignments. But what is that teaching? I think with many aids these days, including using AI at various stages. When teachers limit students to pencil and paper, this creates a false environment that in no way reflects the kinds of thinking skills they will need in the real world of today.

Yes, we need to train our students to communicate their thinking effectively. However, we also must accept that no one communicates without technology.

Good thinkers use a variety of tools to create. I didn’t go to the library to write this blog. I used Google. I used AI-powered grammar checkers that help me avoid bad writing habits (which don’t like the fact that I used “I” to start five sentences in a row). I even used ChatGPT to see if my prose was telling the story that I wanted to tell. I shared my thoughts on LinkedIn, not a scholarly journal. Are those uses of technology cheating?

The days of oral poetry are thousands of years in the past. Technology will enter the picture somewhere. As Plato implies, writing itself is a technology. However, teachers and academics overlook that digital technology has opened the doors to a range of complementary technologies ranging from webpages to concept maps to comics to photography, and many more.

When we focus on writing as the only technology, we miss the potential for understanding different ways of thinking. Text drives narrative in certain directions. It leads to over-specialization and the fetishization of narrow slivers of knowledge. It is also something that machines like generative AI find easy to mimic even in the iterations we are using today.

Over the last 40 years, we have opened doors to new ways of expressing our thinking that the educational community has largely ignored. Artificial intelligence, which I prefer to call “augmented” intelligence, augments our ability to think as well as communicate in unprecedented ways. When we don’t teach learners to think in an AI world, we are doing them an immense disservice.

Instead, we should structure our educational experiences to incorporate every tool we can lay our hands on instead of insulating our students from change. If our educational systems don’t do this, society will find replacements for them. The graduates that we produce will be the actual victims here. We need thinkers more than ever today.

Generative AI can be a partner in understanding what our students are thinking. It reduces the friction between thought and narrative. I have found it an invaluable tool for gaining insight into what my students are thinking in real time. This alone makes it far more powerful than any paper or essay they could write.

Technology provides us with tools we can use to figure out what others are thinking. When we fetishize writing, we confuse means with ends. Writing is a means. Thinking is the end. We should teach thinking and use every technological tool we can find to achieve that end. To achieve this, it’s time to stop worrying about protecting the means of getting there because that’s what we’re used to and lean forward in our teaching strategies.